Comprehensive Virome Profiling of Apple Mosaic Disease-Affected Trees in Iran Using RT-PCR and Next-Generation Sequencing by Anahita Hamedi, Farshad Rakhshandehroo, Mohammad Reza Safarnejad, Gholamreza Salehi Jouzani, Amani Ben Slimen, Toufic Elbeaino

“…In this study, 170 apple leaf samples representing various commercial cultivars were collected across the country. …”
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FLWD:A Webshell detection method based on federated learning by ZENG Qingpeng, CHAI Jiangli, WU Shuixiu

“…To address these challenges, a Webshell detection method based on federated learning was proposed. …”
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Multi-scale attention-enhanced deep learning approach for detecting seven trunk pests and diseases in Shanghai’s urban plane trees by Tianyang Song, Guohua Hu, Tianci Yu, Xing Meng, Yanting Zhang, Ruiqing Yang, Benyao Wang, Xia Li

“…Robustness was validated through experiments with varied parameters, repeated training sessions, and stratified sampling addressing class imbalance. This research demonstrates the model's potential for intelligent, automated monitoring of urban tree health.…”
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Molecular detection and phylogenetic diversity of Staphylococcus aureus isolated from goat subclinical mastitis in Nineveh governorate by Ayman H. Taha, Omar H. Sheet, Dhyaa M. Jwher

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Detecting Potential Investors in Crypto Assets: Insights from Machine Learning Models and Explainable AI by Timotej Jagrič, Davor Luetić, Damijan Mumel, Aljaž Herman

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Molecular Detection and Phylogenetic Analysis of Cucumber Mosaic Virus Infecting Bhut Jolokia (Capsicum chinense Jacq.) of Assam by Munmi Borah, R. Gowtham Kumar, Sundaresha Siddappa

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A Multifeature Fusion Network for Tree Species Classification Based on Ground-Based LiDAR Data by Yaoting Liu, Yiming Chen, Zhengjun Liu, Jianchang Chen, Yuxuan Liu

“…Light detection and ranging (LiDAR) holds considerable promise for tree species classification. …”
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Detection of 16S rRNA Methylases and Co-Resistance with β-lactams among Klebsiella pneumoniae Isolates from Iraqi Patients by Mustafa et al.

“…Out of 150 clinical samples, 50 isolates of Klebsiella pneumoniae were identified according to morphological and biochemical properties. …”
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Detecting anomalies in blockchain transactions using machine learning classifiers and explainability analysis by Mohammad Hasan, Mohammad Shahriar Rahman, Helge Janicke, Iqbal H. Sarker

“…This algorithm is compared against other commonly used under-sampling and over-sampling techniques. Finally, the outcomes of various tree-based single classifiers are compared with those of stacking and voting ensemble classifiers. …”
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Automatic training sample collection utilizing multi-source land cover products and time-series Sentinel-2 images by Yanzhao Wang, Yonghua Sun, Xuyue Cao, Yihan Wang, Wangkuan Zhang, Xinglu Cheng, Ruozeng Wang, Jinkun Zong

“…Secondly, a locally selective combination in parallel outlier ensembles (LSCP) anomaly detection algorithm was applied to filter abnormal samples. …”
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Rotating Machinery Fault Detection Using Support Vector Machine via Feature Ranking by Harry Hoa Huynh, Cheol-Hong Min

“…Fifty-eight features were ranked using the Decision Tree model to identify the essential features as the classifier predictors. …”
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Spatiotemporal Land Use Change Detection Through Automated Sampling and Multi-Feature Composite Analysis: A Case Study of the Ebinur Lake Basin by Yi Yang, Liang Zhao, Ya Guo, Shihua Liu, Xiang Qin, Yixiao Li, Xiaoqiong Jiang

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Detection and Molecular Characterization of ‘Candidatus Phytoplasma Trifolii’, a Member of the Clover Proliferation Grup, Infecting Tomato Plants from Iğdır Province in Turkey... by Mustafa Usta, Abdullah Güller

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Improving Early Detection of Dementia: Extra Trees-Based Classification Model Using Inter-Relation-Based Features and K-Means Synthetic Minority Oversampling Technique by Yanawut Chaiyo, Worasak Rueangsirarak, Georgi Hristov, Punnarumol Temdee

“…The early detection of dementia, a condition affecting both individuals and society, is essential for its effective management. …”
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Design of an Iterative Method for Malware Detection Using Autoencoders and Hybrid Machine Learning Models by Rijvan Beg, R. K. Pateriya, Deepak Singh Tomar

“…In the evolving cyber threat landscape, one of the most visible and pernicious challenges is malware activity detection and analysis. Traditional detection and analysis methods face threats of data high-dimensionality, lack of strength against adversarial attacks, and non-efficient use of unlabeled data samples. …”
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Epidemiology of Helminthic Infections and Phylogenetic Tree of Strongyloides stercoralis in Rubber Tree Plantation in Lower Northern Part of Thailand by Phuangphet Waree Molee, Apichat Vitta, Somchai Saengamnatdej

“…The specific goals include assessing prevalence using Formalin Ethyl–acetate Concentration Technique (FECT) and Agar Plate Culture (APC) and constructing S. stercoralis phylogenetic tree. Methods: Overall, 646 fecal samples from rubber plantation workers in five provinces in northern Thailand were examined using FECT and APC under microscope. …”
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A Fast and Cost-Effective Electronic Nose Model for Methanol Detection Using Ensemble Learning by Bilge Han Tozlu

“…In this study, an electronic nose system was designed using 11 inexpensive gas sensors to detect the proportion of methanol in an alcohol mixture. …”
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ResTreeNet: A Height-Aware LiDAR Tree Classification Model With Explainable AI for Forestry Applications by Asrat Kaleab Taye, Jeong-Mook Park, Hyung-Ju Cho, Jin-Taek Kang, Yeon-Ok Seo

“…Light detection and ranging (LiDAR) technology, capturing highly detailed 3D structural information of vegetation, has become a powerful tool for automated tree classification. …”
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Molecular detection by some virulence genes of Salmonella enterica subsp. enterica isolated from the stool of children with diarrhea by Mohammed Nadhir Maaroof, Ahmed Hussein Dhayea

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A comparative study of machine learning algorithms for fall detection in technology-based healthcare system: Analyzing SVM, KNN, decision tree, random forest, LSTM, and CNN by Afuan Lasmedi, Isnanto R. Rizal

“…This study aims to compare the performance of six classification algorithms: Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Decision Tree, Random Forest, Long Short-Term Memory (LSTM), and Convolutional Neural Networks (CNN) in detecting fall incidents using wearable sensor data such as accelerometers and gyroscopes. …”
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